excess weight and covid-19...living with obesity to lose weight, together with interventions to...

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Excess Weight and COVID-19 Insights from new evidence


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About Public Health England Public Health England exists to protect and improve the nationrsquos health and wellbeing and reduce health inequalities We do this through world-leading science research knowledge and intelligence advocacy partnerships and the delivery of specialist public health services We are an executive agency of the Department of Health and Social Care and a distinct delivery organisation with operational autonomy We provide government local government the NHS Parliament industry and the public with evidence-based professional scientific and delivery expertise and support Public Health England Wellington House 133-155 Waterloo Road London SE1 8UG Tel 020 7654 8000 wwwgovukphe Twitter PHE_uk Facebook wwwfacebookcomPublicHealthEngland Prepared by Jamie Blackshaw Alison Feeley Lisa Mabbs Paul Niblett Elizabeth Atherton Rachel Elsom Estella Hung Dr Alison Tedstone and other members of PHE

copy Crown copyright 2020 You may re-use this information (excluding logos) free of charge in any format or medium under the terms of the Open Government Licence v30 To view this licence visit OGL Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned Published July 2020 PHE publications PHE supports the UN gateway number GW-1405 Sustainable Development Goals


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Contents

Acknowledgements 4

Glossary of terms 5

Executive summary 6

Key insights 9

1 Introduction 11

2 Scale of obesity prevalence and risk to health 14

3 Obesity and risks to health 19

4 Inequalities relating to obesity 21

5 Excess weight and COVID-19 24

6 Obesity and COVID-19 Potential plausible mechanisms 33

7 Potential benefits of healthier weight 36

8 Drivers of obesity 38

9 Concluding remarks 46

Appendix 1 Summary information on study design of UK studies 48

References 56


4

Acknowledgements

Public Health England (PHE) would like to thank the following peer reviewers and colleagues for their expertise and insight that has shaped the development of this resource Naveed Sattar Professor Metabolic Medicine Institute of Cardiovascular and Medical Sciences University of Glasgow Susan Jebb Professor of Diet and Population Health University of Oxford and John Wilding Professor of Medicine and Honorary Consultant Physician Aintree University Hospital


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Glossary of terms

Body mass index (BMI) definition BMI is an estimate of body mass and is calculated by dividing a personrsquos weight by the square of their height Table 1 BMI classification

BMI Range BMI Category

Less than 185kgm2 Underweight

185 to lt25kgm2 Healthy weight

25 to lt30kgm2 Overweight

30 to lt40kgm2 Obesity

40kgm2 or more Severe obesity

Excess weight Classified by the National Institute for Health and Care Excellence (NICE)1 as an adult living with overweight obesity or severe obesity with a BMI ge25kgm2 BMI cut-off for treatment services are lower for Black Asian and Minority Ethnic (BAME) groups than White groups2 23kgm2 indicate increased risk and 275kgm2 indicate high risk respectively Weight management support Weight management services in England are offered at different lsquotiersrsquo or level of intervention Tier 1 includes universal prevention services such as health promotion tier 2 includes multicomponent behaviour change and often takes the form of group-based support run by commercial providers tier 3 is specialist multi-disciplinary weight management and tier 4 includes bariatric surgery


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Executive summary

This report provides evidence-based insights on the relationship between excess weight and COVID-19 Evidence has been brought together from UK and international studies published during the pandemic These have been identified using a pragmatic methodology the report is not a systematic review Findings have been contextualised with information on the prevalence causes and risks of excess weight Information on food and drink purchases and physical activity during lockdown is also included The prevalence and disease burden resulting from excess weight is a major international public health concern Almost two-thirds of adults in England are living with excess weight for their height (BMI ge25kgm2) with similar figures in Scotland Wales and Northern Ireland Excess weight affects all population groups but is higher for those people aged between 55-74 years people living in deprived areas and in some Black Asian and Minority Ethnic (BAME) groups compared with the general population It is established that the health risk of excess weight for some BAME groups occur at a lower BMI than for White populations Living with excess weight is a risk factor for a range of chronic diseases including type 2 diabetes cardiovascular disease many cancers liver and respiratory disease Obesity is also associated with reduced life expectancy and lower quality of life Evidence on the links between weight status and COVID-19 outcomes are drawn primarily from three sources retrospective cohort studies clinical audits of patients with COVID-19 in hospital and routine primary care records with data linkage to outcomes This evidence suggests excess weight is associated with an increased risk of the following for COVID-19 a positive test hospitalisation advanced levels of treatment (including mechanical ventilation or admission to intensive or critical care) and death The risks seem to increase progressively with increasing BMI above the healthy weight range even after adjustment for potential confounding factors including demographic and socio-economic factors There is also some evidence to suggest that disparities in excess weight may explain some of the observed differences in outcomes linked to COVID-19 for older adults and some BAME groups


7

These observations are supported by plausible mechanisms which might explain the association between obesity and COVID-19 outcomes These include the effects of excess adipose tissue on respiratory function metabolic dysfunction the cardiovascular system enhanced inflammatory response and impaired response to infection There may also be an interaction with weight-related comorbidities including type 2 diabetes cardiovascular and respiratory diseases which are also associated with more severe COVID-19 In addition socio-economic and demographic factors associated with excess weight are also associated with COVID-19 severity Stigma experienced by people living with obesity may delay interaction with health care and may also contribute to increased risk of severe complications arising from COVID-19 Rapid emergence of research relating to excess weight and COVID-19 has been vital in supporting policy and decision makers However there remain limitations with the evidence to date including unrepresentative sampling small sample sizes in many studies or limited numbers of COVID-19 infections In addition BMI has been estimated and not measured in some studies or measured many years prior to exposure to COVID-19 infection There is much more to understand when it comes to obesity and the pathogenesis of COVID-19 including why some population groups appear to have greater risk Nonetheless despite its limitations the evidence consistently suggests that people with COVID-19 who are living with overweight or obesity compared with those of a healthy weight are at an increased risk of serious COVID-19 complications and death Some of the studies suggest that the association is attenuated by but independent of other important factors including age sex and ethnicity It is also independent of social economic status in studies which considered this At this time however conclusions on excess weight and COVID-19 severity are tentative and more research is needed to build the evidence base It is currently unclear to what extent the relatively high prevalence of excess weight seen in the UK compared with other countries may have contributed to the severity of COVID-19 in the UK In addition it is uncertain to what extent differences in the prevalence of excess weight for different population groups (including for different ethnic groups and those living in deprived areas) have contributed to inequalities in outcomes However these inequalities related to obesity appear to be key factors in the risk of COVID-19 For groups living with obesity weight loss has been shown to bring long-term health benefits There is currently no high-quality research on the effects of weight loss on COVID-19 risks however based on the potential mechanisms


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underpinning the associations the role of excess weight as a risk factor for serious COVID-19 complications warrants further consideration Factors such as age and ethnicity cannot be changed and factors such as deprivation are complex to address Supporting people who are overweight or living with obesity to lose weight together with interventions to prevent or slow weight gain across the population will plausibly reduce future population risks of COVID-19 Moreover there is robust evidence these interventions will bring wider health benefits to individuals and reduce pressures on the NHS due to overweight and obesity There is no single solution to tackling obesity Actions will be required to both prevent excess weight gain and support people who are living with overweight or obesity to move towards a healthier weight Drivers of excess calorie intakes and low levels of physical activity within the environment people live will need to change at a national and local level to support population-level weight change Improving and increasing access to weight management options for the large numbers of people who could benefit and which are tailored to individual needs and preferences would also help address levels of obesity The COVID-19 pandemic has brought the health crisis caused by overweight and obesity to the fore The case for action at scale and over the long term to prevent excess weight and support people living with obesity is strong Doing more for those groups most affected can help improve health overall and help address some of the inequalities in health


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Key insights

What we knew about excess weight pre-pandemic

bull most adults in England are living with overweight or obesity (63 are gt25kgm2) some groups have higher levels than others including those aged between 55-74 years those living in deprivation and some BAME groups

bull as BMI increases above the healthy range (185 to lt25kgm2)i it is a risk factor for a wide range of chronic diseases including type 2 diabetes cardiovascular disease many cancers liver and respiratory disease and premature mortality increases

bull it is hard to study the effect of weight loss on diseases that take many years to develop such as cancer however evidence shows that reducing weight towards a healthier BMI range improves biological markers associated with better health (such as blood pressure) and reduces the risk of type 2 diabetes and improves quality of life scores depression and mobility

New evidence on COVID-19 and health

bull there are a number of limitations in the evidence to date including sampling and testing strategies unequal exposure to COVID-19 sample sizes and limited number of COVID-19 infections More research is needed

Laboratory confirmed COVID-19

bull as BMI increases above the healthy range (20 to lt25kgm2)1 there is an association with testing positive with COVID-19 (may be subject to possible selection bias)

bull BMI is more strongly related to testing positive with COVID-19 in BAME groups compared with White ethnic groups

bull Findings in this section may be particularly affected by selection bias primarily due to the testing strategy in place at the time the studies were carried out

Hospitalisation

bull patients with COVID-19 living with overweight (BMI ge25kgm2) or obesity (BMI ge30kgm2) compared with patients with a healthy weight (BMI 20 to lt25kgm2) are more likely to be hospitalised if infected with COVID-19

i Healthy range of BMI is 185 to 249kgm2 Some of the studies cited in this report refer to a healthy range of 20 to lt25kgm2


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bull patients living above a healthy weight (BMI ge25kgm2) are at a progressively increased risk of being hospitalised compared with patients with a BMI lt25kgm2

Admission to intensivecritical care and treatment

bull patients living with overweight or obesity (BMI ge25kgm2) compared with patients with a BMIlt25 kgm2 are more likely to be admitted to intensivecritical care and to require advanced treatment for severe COVID-19 symptoms

Risk of mortality bull there is potentially a higher risk of COVID-19 related death with increasing

BMI bull where studies have adjusted for confounding factors such as age sex

measures of socio-economic status (SES) ethnicity and co-morbidities the relationship between excess weight and COVID-19 risk has persisted


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1 Introduction

It is established that excess body weight is one of the leading causes of poor health in Britain3 This is because most of the population carry excess body weight which is known to increase the risk of a range of chronic diseases including type 2 diabetes many cancers liver disease and cardiovascular diseases4 5 6 New evidence from studies in the UK and around the world provide evidence about excess weight and its association with COVID-19 This report collates insights from this evidence on bull the prevalence causes and other health risks of overweight and obesity bull food purchases and physical activity during lockdown bull drivers of excess weight what is and could be done to tackle the problem

and where more action is needed Much of the information provided is drawn together from existing technical reports policy and strategy documents public health and clinical guidance and published academic evidence The publication is intended to provide insights to inform policy and practice when it comes to supporting people living with obesity It is aimed at policy makers in national and local government local public health teams health professionals who have an interest in obesity and treating COVID-19 charities and organisations supporting people living with obesity academics and other colleagues working in the health and social care sector It is also intended to support health marketing campaigns COVID-19 is an infectious disease which is caused by a novel coronavirus Many people infected with COVID-19 can suffer a range of mild to moderate respiratory disease and symptoms such as high temperature a persistent cough and sore throat Many can also be symptomless However for some people COVID-19 will cause more severe symptoms and it can adversely affect the lungs and many other body systems and it can cause death7 On the 12 March the World Health Organization characterised COVID-19 as a pandemic7 Up until the 24 July 2020 there were 297146 confirmed cases in the UK with over 45550 people dying because of COVID-198


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Some people are more at risk of developing serious illness if infected by COVID-19 including older people and people with underlying medical conditions including amongst others cardiovascular disease diabetes chronic respiratory disease and current or recent cancer People living with severe obesity (BMI ge40kgm2) are also deemed to be clinically more vulnerable9 Understanding how COVID-19 affects different groups in the population is important to help protect people from the disease PHE analysed COVID-19 diagnosis data and published a report which demonstrated that COVID-19 has a disproportionate impact on certain population groups including people living in more deprived areas (Figure 1) and BAME groups (Figure 2)10 Some of these population groups are also disproportionally affected by obesity (see Section 4) At the time of publication treatment includes steroids and dexamethasone for severely ill people There are many trials ongoing to develop and test vaccines and research into treatments for COVID-19 and there is also research underway to understand the factors that are associated with risk of severe symptoms associated with COVID-19 This includes investigating who may be affected more by the disease and how conditions such as living with overweight or obesity might impact on how the body responds to being infected with COVID-19


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Figure 1 Age standardised diagnosis of COVID-19 rates by deprivation quintile and sex as of 13 May 2020 England

Source PHE Second Generation Surveillance System

Figure 2 Age standardised diagnosis rates of COVID-19 by ethnicity and sex as of 13 May 2020 England



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2 Scale of obesity prevalence and risk to health

63 of adults in England are above a healthy weight with 36 and 28 of adults living with overweight or obesity respectively Two-thirds of men are living with overweight or obesity (67) and 6 out of 10 women are living with overweight or obesity (60) One out of 4 men is living with obesity (26) and 29 of women are living with obesity11 Annexe A Table 3 to this publication provides data on levels of adults living with severe obesity Overweight and obesity tend to increase with increasing age with the lowest prevalence in 16-24-year olds This peak occurs for men at the 55-64-year age group (82) and in the 65-74-year age group in women (70) followed by a decline in the oldest age group for men and women Figurersquos 3 and 4 present prevalence rates by age for men and women respectively Figure 3 Prevalence of men living with overweight and obesity by age (Health Survey for England (HSE) 2018)

Adult (aged 16+) BMI thresholds Overweight 25 to lt30kgm2 Obese ge30kgm2


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Figure 4 Prevalence of women living with overweight and obesity by age (HSE 2018)

Adult (aged 16+) BMI thresholds Overweight 25 to lt30kgm2 Obese ge30kgm2 Figure 5 presents the prevalence of obesity among adults and shows that this varies by region in England with the highest prevalence in the West Midlands and the lowest prevalence in London and the South East


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Figure 5 Prevalence of men and women living with obesity by England region (HSE 2018)

Obesity prevalence is age standardised 95 confidence intervals are shown Adult (aged 16+) obesity BMI ge30kgm2 Trends projections and international comparators

Figure 6 presents data demonstrating that obesity prevalence increased steeply between 1993 and around 2000 with a slower rate of increase after Figure 6 Trend in obesity prevalence data for adults aged 16+ 1993 to 2018 (HSE 2018)

Adult (aged 16+) obesity BMI ge30kgm2


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Figure 7 presents an analysis of obesity prevalence trends carried out for the Health Profile for England 201912 This includes forecast data up to 2024 which suggests that without intervention obesity rates will continue to rise among the adult population However it is not known what effect the pandemic might have on future trends of obesity Figure 7 Trend in prevalence of adults living with obesity aged 16+ 2007 to 2018 PHE forecasts 2018 to 202412


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Obesity prevalence in the UK compared with other Organisation for Economic Co-operation and Development (OECD) countries

Figure 8 provides comparisons for OECD countries based on data for 2017 adults aged 15 and over or closest available Data is for 2017 or nearest available year Only countries with measured data are included here The UK reports an adult obesity level of 26 This is 14 percentage points lower than the US which reports the highest adult obesity level Japan and Korea report obesity levels of less than 1013 Figure 8 Prevalence of adults living with obesity in OECD countries (OECD 2017)

Measured data only (excludes countries with only self-reported data)


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3 Obesity and risks to health

Population levels of obesity have resulted in significant disease burden14 Compared with individuals of a healthy weight (BMI 18middot5ndash24middot9kgmsup2) life expectancy from age 40 years was 4middot2 years shorter in men living with obesity (BMI ge30kgmsup2) and 3middot5 years shorter in women living with obesity furthermore for a BMI gt40kgm2 life expectancy was reduced by 91 years for men and 77 years for women15 Living with obesity seriously affects peoplersquos quality of life and their health It increases the risk of hypertension heart attacks stroke heart failure type 2 diabetes non-alcoholic fatty liver disease and some cancers in adults 4 5 6 Obesity is the second biggest preventable cause of cancer in the UK with more than 1 in 20 cancer cases caused by excess weight16 These diseases for which obesity is a risk factor are over represented in patients diagnosed with COVID-19 in hospital or with more severe COVID-1917 Each year 20 of people in the UK see a doctor about a musculoskeletal problem (such as osteoarthritis) Seven in 10 people who report living with a long-term musculoskeletal problem are either living with overweight or obesity18 There are multiple risk factors that can heighten peoplersquos susceptibility to musculoskeletal problems in addition to excess weight physical inactivity vitamin D status or calcium smoking older age and genetic predisposition to some musculoskeletal conditions Table 2 shows the extent to which obesity increases the risk of diseases relative to not living with obesity For example a woman living with obesity is 127 times more likely to develop type 2 diabetes than a woman who is not living with obesity Table 2 Relative risk factors for men and women living with obesity compared to men and women not living with obesity of developing selected diseases

Men

Women

Type 2 diabetes 52

127

Hypertension 26

42

Myocardial infarction 15

32


20

Cancer of the colon 30

27

Angina 18

18

Gall bladder diseases 18

18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13

Source National Audit Office 2006 as referenced in Statistics on Obesity Physical Activity and Diet England 200619 Compared with people with a healthy weight those people living with obesity are more likely to experience respiratory issues including obstructive sleep apnoeahypopnoea Obesity is also associated with asthma20 Mental health problems are also associated with obesity21


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4 Inequalities relating to obesity

Socio-economics

Deprived areas have higher levels of overweight and obesity compared with more affluent areas in England22 23 A higher prevalence of excess weight is also seen in some BAME groups and the health risks of obesity arise at a lower BMI Like the PHE Disparities report some studies looking at ethnicity social differences and disparities associated with COVID-19 indicated that age and gender ethnicity geography and deprivation are associated with poorer COVID-19 outcomes24 25 26 Obesity prevalence is highest among the most deprived groups (gt34) compared with just over 20 in the least deprived groups Figure 9 shows that around 20-21 of men and women in the least deprived quintile compared with 35 men and 37 women in the most deprived quintile were living with obesity Analyses of HSE 2018 data (Annexe A Table 3) indicates that the prevalence of men and women living with severe obesity increases with level of deprivation Figure 9 Prevalence of adults living with obesity by deprivation HSE 2018

Obesity prevalence is age standardised 95 confidence intervals are shown Adult (aged 16+) obesity BMI ge30kgm2


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Ethnicity

As illustrated in Figure 10 differences are also seen in the prevalence of obesity between different ethnic groups Obesity among Black women is 536 White women 275 and Asian women 236 Obesity among men was similar for Black men (277) and White men (273) and lowest among Asian men (163)27 An important consideration to the information presented here is that cardiometabolic health risks of excess weight occur at a lower BMI for BAME groups compared to White groups Accordingly the BMI thresholds for intervention are set at a lower level (BMI 23kgm2 to indicate increased risk and 275kgm2 to indicate high risk) than for White groups1 Figure 10 Prevalence of adults living with obesity by ethnic group HSE 2017

The disproportionate burden of COVID-19 on certain groups such as people living in more deprived areas and some BAME groups overlaps with variations in the prevalence of obesity Evidence in the PHE Disparities report and commentary from Lassale et al in an analysis of the ethnic disparities on hospitalisation with COVID-19 reflect that ethnic minority groups are often living in more deprived areas It is not uncommon for some BAME families to live as part of intergenerational and or larger households Some BAME groups may be


23

more likely to be exposed to infection due to their employment for example in public and community facing jobs exposing them more to infection10 24 28 Other groups are also disproportionally affected by obesity compared with the general population including people living with severe mental illness or learning disabilities The prevalence of obesity is almost double in adult patients aged 15-74 years with severe mental illness compared with all patients29 Published data in 2016 for people with learning disabilities reports that more men and women were living with obesity (BMIge 30kgm2) 31 and 45 compared with 24 of men and 27 of women without a learning disability30


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5 Excess weight and COVID-19

Between mid-April and July PHE has monitored the evidence relating to COVID-19 and obesity particularly in relation to diagnosis and risk of illness including hospital and ICU admission the need for advanced treatment and mortality Evidence was identified through routine obesity literature scans and contact with experts Information was extracted from studies into a standard template on an ongoing basis and reviewed and checked by at least two other people PHE has not undertaken a systematic or complete review of the literature however checks have been undertaken with experts in the field to ensure key studies have been identified and for accuracy of interpretation Data extraction tables have been replicated in this publication for the UK studies (Annexe A Table 1) and adapted to provide summaries of studies from other countries (Annexe A Table 2) Several issues that may limit the interpretation and should be considered when reviewing the studies that are summarised in this section include that bull the studies published to date have mostly analysed data on hospitalised

patients with COVID-19 of which some comprise of very small samples This makes findings from individual studies non-generalisable due to bias towards people with severe illness

bull all people in studies admitted to or in hospital have proven COVID-19 infection There may be differences in characteristics of people who do not seek help or in their timing of admission to hospital in relation to disease progression or unknown variations in viral load

bull there is uncertainty on which people in the population were infected (in prospective cohort studies) with potential differences in patterns of infection by BMI ethnicity or deprivation

bull many adjustment factors have varied in different studies with some potentially over adjusting either for parameters related to disease severity or for parameters potentially mediating the link between obesity and COVID-19 and other studies not adjusting for relevant factors such as deprivation

bull in the UK most of the current studies have used the UK Biobank dataset This is a large set of data following half a million people who volunteered to participate and researchers have linked data to confirmed COVID-19 tests It is important to note that BMI measurements would be relatively outdated and some authors stated measurement was 12 years old However adult BMI levels generally track over time The data on prevalence rates is not


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representative of the general population However whilst prevalence rates may not be generalisable they are deemed to provide valid assessments of disease exposure and relationships31

bull some of the evidence reviewed has been rapidly published and in some cases gone through rapid review so could be subject to unchecked errors

bull there is likely variation in how and when in relation to subsequent COVID-19 outcomes height and weight andor BMI is assessed in these data sources whether through anthropometric measurements (height and weight) existing patient records self-reported or assessed in some other way Therefore some peoplersquos BMI and hence categorisation is likely to have been assessed incorrectly Also not all studies have used the same BMI thresholds or have combined them to classify levels of overweight and obesity

Evidence from systematic reviews on the association between excess weight and COVID-19 severity

Two of the most recent systematic reviews are described in this section Not all studies captured in this report were included in the reviews Yang et al32 (2020) conducted a systematic review with meta-analysis to assess the relationship between BMI and obesity and severity of COVID-19 based on literature searches up until 21 April 2020 The review included 9 case-control and retrospective cohort studies 8 of which were included in the meta-analyses Seven of the 9 studies were conducted in China while 2 studies were conducted in France and the US At least 2 studies conducted in China used a BMI cut-off for obesity of gt24kgm2 while the studies conducted in France and the US used the WHO diagnostic criteria of ge30kgm2 The review authors did not define disease severity In this systematic review based on the findings of 6 studies including 667 patients patients with severe COVID-19 had a higher BMI compared with patients with mild COVID-19 (WMDii) 267 BMI units 95 confidence interval (CI) 152 to 382) In addition patients with obesity had more severe COVID-19 outcomes compared to patients without obesity (Odds Ratio (OR) 231 95CI 130 to 412) based on the findings of 4 studies that included 2644 patients The pooled estimates of the association between obesity and COVID-19 severity should be interpreted with caution as it is unclear whether these were based on individual effect estimates that had been adjusted for key confounding factors ii Weighted mean deviation


26

including age sex ethnicity and the existence of co-morbidities such as hypertension and type 2 diabetes although such conditions may also in part mediate the link between obesity and more severe outcomes Only 2 of the 9 included studies explicitly identified co-morbidities 1 of which also stratified its sample by age Given the potential for residual confounding the pooled results may have overestimated the association between obesity and COVID-19 severity Hussain et al33 (2020) conducted a meta-analysis to investigate whether patients living with overweight or obesity were more likely to die from COVID-19 compared to patients with a healthy weight Fourteen studies including 403535 patients with COVID-19 from various countries (including at least 5 conducted in Chinese patients) the latest study included was published 9 July 2020 Although the review contained some retrospective analyses the design of some of the studies including those coming from the unpublished literature was unclear Compared with patients living with a healthy weight patients living with overweight or obesity (defined as having a BMI gt25kgm2) were more likely to die (OR 368 95 CI 154 to 883) need advanced respiratory support (OR 698 95 CI 537 to 907) and be critically ill from COVID-19 (OR 203 95 CI 175 to 236) The review did not specifically analyse the risk of COVID-19 outcomes in patients living with obesity BMI ge30kgm2 The results from this meta-analysis should be interpreted with caution The pooled estimates had high heterogeneity (I2gt80) which was inadequately investigated by the review authors The pooled results may also overestimate the association between higher BMI and COVID-19 outcomes Only 5 of the 14 included studies controlled for confounding factors In addition it is unclear whether existing comorbidities such as hypertension and type 2 diabetes which whilst may mediate the association between obesity and risk of severe COVID-19 outcomes were accounted for Evidence from individual studies on the association between weight status and COVID-19 diagnosis and severity

Twelve UK studies reported analysis relating to obesity (see Annexe A Table 1) Seven used UK Biobank data linked to testing positive for COVID-19 34 35 36 37

38 39 40 3 explored hospital data 41 42 43 and 3iii linked primary care data to testing positive for COVID-19 Hospital Episode Statistics (HES) and Office for National Statistics (ONS) deaths 44 45 46 Intensive care data is also presented collated by the Intensive Care National Audit and Research Centre (ICNARC) 47

iii Williamson et al pre-publication and final peer reviewed publication are included (references 44 and 45 respectively)


27

Summary information on the study design of the 12 studies including reported limitations is included in Appendix 1 Information on relevant confidence intervals are included in Annexe A Table 1 Nineteen studies from other countries (China France Italy Mexico and the USA) are included see Annexe A Table 2 These studies were retrospective or cross-sectional data analyses of a relatively small number of cases of hospitalised patients 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 and of larger numbers of patients64 65 66 Information on adjustments made during data analysis are noted The details of the results are described in Annexe A including where there is significance


One UK study Yates et al used UK Biobank of over half a million participants linked to COVID-19 test data in which 882 patients tested positive for COVID-19 Adjusted for a range of possible confounding factors the authors reported a dose response association between BMI or waist circumference and a positive test for COVID-19 in people with overweight obesity and severe obesity of 1middot31 155 and 1middot57 respectively compared with healthy weight range34 The authors acknowledge that their findings are limited by possible selection bias

Hospitalisation

In the UK there have been several studies using UK Biobank data linked to diagnosis for COVID-19 which have reported that individuals living with overweight or obesity were more likely to be tested positive in a hospital setting than individuals with a healthy weight36 37 For instance Hamer et al reported that compared with patients with BMI lt25kgm2 those living with overweight or obesity had an increased risk of hospitalisation RR 132 and 197 respectively (after adjusting for age sex education ethnicity diabetes hypertension cardiovascular disease)35 In New York Petrilli et al reported that people living with obesity (BMI 30-399kgm2) or severe obesity (BMI ge40kgm2) and diagnosed with COVID-19 (median age of 52 years) were 4 and 6 times respectively more likely to be hospitalised compared with patients with COVID-19 and a BMIlt30kgm2 61 In another US study Bhasin et al analysed a subset of patients less than 50 years of age hospitalised with COVID-19 without diabetes or hypertension Mean BMI was greater than those gt50 years of age The authors reported an inverse relationship between BMI and age amongst patients hospitalised with COVID-19 Bhasin et al during the same period observed that this BMI to risk association was not present in non-COVID-19 patients54 whilst Sattar et al


28

showed that risk of death from COVID-19 was more strongly associated with increasing BMI in younger adults (lt70 years) when compared with those aged gt70 years40 Admission to intensivecritical care

In England Wales and Northern Ireland data from the ICNARC reported that 313 and 79 of patients critically ill in intensive care units (ICU) with confirmed COVID-19 had a BMI ge30kgm2 or a BMI ge40kgm2 compared with 289 and 29 of the general population respectively (after adjusting for age and sex) This disparity was also seen when looking at severe levels of obesity in White and non-White patients47

Hippisley-Cox et al analysed general practice data for over 8 million people of which 19486 had tested positive for COVID-19 and 1286 were admitted to ICU The authors reported that patients living with overweight (BMI ge25-299kgm2) obesity (BMI ge30-349kgm2) or severe obesity (BMI ge35kgm2) compared with patients with a BMI ge20-249kgm2 had increased odds of ICU admission of 164 259 and 435 (adjusted for age sex ethnicity deprivation co-morbidity treatment and other factors) Figure 11 reproduced a figure depicting the hazard ratios (HR) for ICU admission according to BMI category43


29

Figure 11 reproduced a figure depicting the HR for ICU admission according to BMI category Hippisley-Cox et al QResearch database University of Oxford43

The findings from UK based studies are supported by analyses conducted in a range of studies from different countries (US France Mexico and China) See Annexe A Table 2

Risk of mortality

Williamson et al looked at primary care data on 17 million adults of which there were 10926 COVID-19 deaths44 45 This data showed an increasing risk of death with increasing BMI (fully adjusted for age sex ethnicity deprivation and co-morbidities) with HR 105 140 and 192 for people with a BMI between 30-349kgm2 ge35-399kgm2 and ge40kgm2 respectively relative to BMI lt30kgm2 Docherty et al41 reported that of patients hospitalised in 208 UK hospitals there was a 33 increased risk of mortality (after adjusting for age sex and major comorbidities) for those recognised by clinical staff as living with obesityiv Perez-Guzman et al analysed data on a small number of COVID-19 hospitalised patients in a London trust and reported a lack of association between BMI and mortality (unadjusted analyses) However the authors reported that BMI data was missing for half of the patients which may explain this finding42 The association between obesity a high BMI and COVID-19 related death has also been reported using National Diabetes Audit data which explored the iv The classification of obesity was made by a clinician and it is not clear how this was assessed


30

impact in people with diabetes (type 1 and 2 diabetes) The authors reported that the risk of mortality compared with individuals with a BMI 25-29middot9kgm2 was particularly marked at higher levels of BMI (ge40kgm2) for individuals with both type 1 and type 2 diabetes (HR 233 and 160 respectively) Of interest elevated BMI was less strongly linked to deaths not linked to COVID-19 in people with diabetes during the same period46 Bello-Chavolla et al analysed 51633 subjects with COVID-19 and reported that the presence of obesity explained almost half of the total risk association of diabetes on COVID-19 mortality COVID-19 was also reported to increase the risk of mortality in patients living with obesity compared to those not living with obesity by five-fold The authors also reported that addition of obesity in their analyses to other comorbidities was associated with a significantly increased risk of mortality from COVID-1966 In the US Klang et al and Suleyman et al both reported that BMI ge40kgm2 was independently associated with mortality after adjustment for demographics and co-morbidities 58 63 A small US hospital study of which gt90 of the patients were African American reported that obesity (BMI gt30kgm2) was a predictor for mortality (OR 17) After adjusting for age gender and other comorbidities compared to BMI lt30 kgm2 59 Specific analysis relating to COVID-19 obesity and Black Asian and Minority Ethnic Groups

The level of BMI recommended to refer into weight management services in relation to certain chronic diseases for BAME groups is lower than for White Europeans (WErsquos)1 as health risk increases at a lower level of excess weight Razieh et al used Biobank data linked to PHE laboratory COVID-19 test data The authors stated that their analysis is limited by non-random testing for COVID-19 within the UK but reported that a higher BMI was associated with increased odds of COVID-19 diagnosis for WE and BAME groups However when comparing the two groups the authors reported a greater risk for BAME individuals relative to WE at higher levels of BMI For example at a BMI of 35kgm2 the odds of COVID-19 were 256 times higher for BAME individuals compared with WErsquos At a BMI of 25kgm2 there was no such difference38 Sattar et al also used linked Biobank data to COVID-19 related deaths Out of 839 COVID-19 diagnoses 189 died from COVID-19 The authors reported that increasing BMI was strongly associated with positive diagnosis of COVID-19 and risk of death With regards to ethnicity an increased BMI was more strongly


31

associated with positive diagnosis (Pinteraction = 0010) and death (Pinteraction = 0002) for non-White ethnic groups (mainly South Asians and Afro-Caribbeans) compared with White ethnic groups40 COVID-19 and non-COVID 19 patient comparisons

Some studies have also investigated differences between different patient groups in hospital settings In the UK ICNARC data indicates that a higher proportion of patients living with obesity and severe obesity were admitted to ICU with COVID-19 (313 and 79) compared with a cohort of patients admitted to ICU (before the pandemic) with non-COVID-19 viral pneumonia (235 and 7)46 Ho et al used UK Biobank data linked to COVID-19 diagnoses to compare the risks associated with COVID-19 compared with that of viral pneumonia In an adjusted model a higher BMI compared to a healthy weight was associated with a 124 relative risk of COVID-19 whereas the relative risk for patients and non-COVID-19 viral pneumonia was 113 for the same BMI comparisons (adjusted models)37 Similarly Simonnet et al reported significant differences in the proportion of patients living with obesity or severe obesityv in a COVID-19 cohort compared with a cohort diagnosed with a non-COVID-19 acute respiratory disease (476 vs 252 and 282 vs 108 respectively)48 Caussy et al also reported that the proportions of patients living with obesity and with critical COVID-19 were significantly higher in ICU compared with a cohort of non-COVID-19 patients living with obesity and admitted to ICU (OR 1middot69) after adjusting for age and sex57 Summary

The set of studies referred to in this section summarised in Annexe A provide valuable insights into the association between excess weight and COVID-19 Consideration of this information and future high-quality research is required to inform policy and practice to help prevent weight gain and provide treatment for people living with overweight or obesity The findings so far from several different study types (prospective cohort clinical audits of patients with COVID-19 in hospital and routine primary care

v Simonnet et al reported that the sex distribution and age in the COVID-19 sample were not significantly different from participants in the non COVID-19 cohort


32

records with data linkage to outcomes early systematic reviews and meta-analyses) carried out in the UK and other countries are in broad agreement on the relationship between weight status and COVID-19 outcomes Living with excess weight is being consistently reported to be associated with an increased COVID-19 risk testing positive (noting that much of early testing in the UK was undertaken in hospitals) hospitalisation advanced levels of treatment (including mechanical ventilation or admission to intensive or critical care) and death The risks seem to increase progressively with increasing BMI above the healthy weight range even after adjustment for potential confounding factors including demographic and socio-economic factors There is also some evidence to suggest that disparities in excess weight may explain some of the observed differences in outcomes linked to COVID-19 for older adults and some BAME groups However there are limitations in the current evidence base linking weight status to COVID-19 (outlined earlier in this section) which means that only tentative conclusions can be drawn A key limitation in terms of the analyses conducted included those who have had tests in hospitals At this time it is not possible to be sure if it is excess weight that is directly causing the reported increased risk of COVID-19 for patients who are living with overweight or obesity compared with those of a healthier weight another factor not taken into account or identified in the currently published studies There are a number of other limitations in the evidence to date including sampling and testing strategies unequal exposure to COVID-19 sample sizes and limited number of COVID-19 infections Further research is needed including more systematic reviews and meta-analyses


33

6 Obesity and COVID-19 Potential plausible mechanisms

Along with emerging evidence on the association between obesity and COVID-19 there has been a breadth of published articles describing the potential mechanisms associated with obesity which might interact with the pathology of COVID-19 This section provides key insights into some of the known effects of obesity and excess adipose tissue and which provide for plausible mechanisms that may be linked to COVID-19 outcomes Insights from the body of evidence detailing mechanisms about obesity and influenza may prove relevant to obesity and COVID-19 though the authors of two papers that describe these mechanisms caution that they may not be transferable nor plausible mechanisms or pathways for other viruses which includes COVID-1967 68 When it comes to COVID-19 and excess weight there has not been any mechanistic studies to date However commentators and authors of studies have hypothesised about several mechanisms by which obesity and particularly severe obesity might affect COVID-19 outcomes This includes the distribution in the body and metabolic effects of excess (and ectopic) adipose tissue and how this adversely impacts respiratory function inflammatory response haematological and immune function and how the body responds to infection with COVID-19 Excess adipose tissue and deposition

The physiological implications of obesity including fat deposition around the upper airway and a heavier thorax can directly impact on and reduce lung function which along with the effects of the virus may affect circulating levels of oxygen20 69 Sanchis-Gomar et al69 explored the role of obesity and its interactions with COVID-19 and detailed how adipose tissue due to containing high levels of the angiotensin-converting enzyme 2 (ACE-2 the enzyme that the virus latches onto to gain access to cells) and that this may make adipose tissue more susceptible to infection Hormonal changes linked to adipose deposition have also been speculated to also play a part70


34

Honce and Schultz-Cherry67 described that people living with obesity may experience a higher viral load when infected with influenza virus prolonged and increased viral shedding and that recovery from infection may be affected

Inflammatory and immune response

Obesity is known to induce a pro-inflammatory response which has been suggested to affect the performance of anti-viral treatment of influenza67 Sattar et al71 and Lockhart and OrsquoRahilly70 commented on the plausibility of various mechanisms where obesity is implicated with COVID-19 including an increased inflammatory response in individuals living with obesity and links to cytokine production Simonnet et al48 Petrilli et al61 Chiapetta et al72 and Kim and Nam73 also draw parallels between the pro-inflammatory response associated with obesity and the inflammatory response observed in obesity related chronic diseases and in severe COVID-19 cases Potential mechanisms that have been postulated in relation to obesity and influenza (not COVID-19) describe how hyperinsulinemia or hyperleptinemia may impair the function of T-cells and hence how the immune system responds and adapts to viral infections68 Notably the authors also observe that vaccinated adults living with obesity have a two-fold risk of influenza compared with vaccinated adults not living with obesity It is not known if this is relevant to COVID-19

Thrombosis

Sattar et al reflected on known links between obesity and thrombotic risks important as the hyperimmune response in COVID-19 may cause harm via widespread microvascular thrombosis and a higher risk of venous thromboembolism Links between excess fat and impaired metabolic responses are also relevant given obesity is a major risk factor for diabetes and diabetes appears to be more common in people with severe COVID-1971 Sanchis-Gomar et al69 also commented on how obesity is associated with hypercoagulability and that this may also be an important factor in the observed elevated risk of thrombosis in patients with COVID-19 In the above obesity may increase the risks of infection leading an exaggerated hyperimmune response At the same time obesity may lessen the bodyrsquos ability to cope with the multiple effects of the virus-induced immune response (for example metabolic cardiovascular respiratory thrombotic)


35

Lockhart and OrsquoRahilly70 provided a detailed account of the potential mechanisms and postulated a few hypotheses which if tested in experiments and proven could help make the case for preventative and curative approaches including preventative energy deficit behavioural programmes

Psycho-social factors

In-addition to the biological mechanisms summarised there are psycho-social factors which may impact on people living with obesity It is evident that people living with obesity suffer stigma and discrimination74 Such stigma could mean that people living with obesity are reluctant to access healthcare75 or may delay seeking care until their disease is more advanced Clinicians academics and patient groups with shared interests in obesity have reflected on relevant factors including weight bias and stigma and variations in care and treatment for people living with obesity76 These are important issues particularly when trying to prevent chronic and infectious disease


36

7 Potential benefits of healthier weight

It is hard to study the effects of weight loss on conditions that take many years to develop however multiple shorter-term studies show that there are some health benefits for a range of conditions Given the mechanisms being suggested that link adipose tissue excess weight and COVID-19 it is conceivable that the benefits of weight loss could mitigate COVID-19 severity Intentional weight loss of between 5kgndash10kg in women living with obesity-related illness is associated with lowered risk of death cardiovascular death cancer and diabetes-related death In men those who lost weight intentionally appeared to have a reduced risk of diabetes-related death77 The NICE guidance on behavioural weight management recognises that even modest amounts of weight loss of 5 can benefit health78 Health benefits of weight loss relate to improved cardiovascular risk and reduced osteoarthritis-related disability79 In individuals with pre-diabetes for every kilogram of weight lost there was a 16 reduction in risk for progression to diabetes80 In a metabolic study a 5 weight loss improved multi-organ insulin sensitivity and β cell function and in the same study additional weight loss of 11ndash16 further increased insulin sensitivity in muscle81 The DiRECT trial assessed remission of type 2 diabetes via a primary care-led weight management programme and found that diabetes remission (among a third of patients) was sustained at 24 months which was linked to the extent of sustained weight loss82 The DROPLET study trialling very low-calorie diets showed at 12 months substantial weight loss and greater improvements in cardiometabolic disease83 For cardiovascular disease risk factors there are potentially profound benefits In a retrospective cohort study of 13722 patients (including 2287 patients who underwent bariatric surgery and 11435 matched controls) metabolic surgery was significantly associated with a lower risk of major adverse cardiovascular events (HR 061)84 Diastolic blood pressure and HDL cholesterol are improved with around ge5 to lt10 weight loss85 Systolic blood pressure is also reduced by around 1mmHg per kg weight loss86 In a post-hoc analysis of the Look AHEAD trial there were fewer major adverse cardiac events by 21 for gt10 of body weight lost87 Research has also shown benefits such as quality of life scores depression and mobility


37

bull Quality of Life assessments at 1 year show improvement with weight loss88 bull depression scores reduce with weight loss89 bull mobility improves with weight loss90 bull improvements in self-esteem have also been shown with weight loss88

Other genetic and observational evidence strongly support important causal effects of obesity and potential benefits of weight loss on risks for heart attacks heart failure and chronic kidney disease9192


38

8 Drivers of obesity

Helping people living with overweight or obesity to achieve or maintain a healthier weight is complex There is no single solution and the situation has been decades in the making and is driven by environmental behavioural biological societal and cultural factors and importantly the interaction of these drivers At its simplest level obesity is caused by consuming more calories than the body uses which over time results in excess weight being gained It is estimated that on average adults in England are consuming 200-300 excess calories per day93 Peoplersquos diets are influenced by a range of factors including preferences and habits formed early on in life educational opportunities employment and psychosocial factors that influence behaviours such as family food preferences and meal patterns The environment where people live is a key driver of the unhealthy behaviours causing obesity where the easiest food and drink options are less than healthy and very often the easiest way to get around is by car94 At a population level there remains low consumption (relative compared with at least 5 portions a day) of fruit and vegetables95 Food and drinks high in sugar fat salt and calories are abundant and for most people are easily accessible The many choices people make are driven by multiple factors including price availability advertising and promotions There are also more food outlets than ever before and takeaways and food deliveries have been made very easy with the growth of digital apps96 The burden of poor diet and obesity is not equal and falls disproportionately on people in underserved communities often living in more deprived areas22 23 97 Areas with more fast-food outlets98 more advertising and less access to green space than those that are more affluent99 Life is much more sedentary than ever before and physical activity which uses up energy plays a role in maintaining a healthier weight including the prevention of weight gain and reduction in body fat It also plays a role in the prevention of weight regain after weight loss78 Increasing physical activity also independently offers benefits to health and most people including those living with obesity can reduce their risk of cardiovascular disease and improve their health by being physically active In combination with calorie deficit diets physical activity can support maintenance of weight loss


39

Food purchasing and physical activity during lockdown

Insights provided here explore changes to dietary and physical activity behaviour during lockdown which are relevant to obesity Most of the regular surveys to monitor what people are doing have been suspended during lockdown so it is not possible to get a full picture of diets physical activity or any body weight changes Currently available evidence is limited However there have been large shifts in where food is purchased and the types of food being bought In pre-lockdown around three quarters of energy intake came from foods consumed at home mainly from supermarkets and other retailers Around a quarter of energy intake came from eating out mainly from outlets such as cafes restaurants and canteens or as complete ready to eat meals from takeaways or deliveries95 Volume sales of food for consumption in the home has increased by 115 for the current calendar year up to 21 June 2020 when compared to the same period last year100 This is likely to reflect in part closure of some food outlets It is not however clear the net effect this had had on energy consumed or diet composition Figure 12 shows an increase in volume sales of food and drink purchased for consumption at home leading up to a peak in the week ending 22 March which was the day before lockdown was announced on 23 March Volume sales for the week ending 22 March were the highest recorded even surpassing the peak at Christmas Volume sales fell heavily in the following week ending 29 March which may reflect the amount of stock piling (which took place in the previous few weeks) the difficulty in purchasing certain grocery products due to a lack of supply and the introduction of lockdown measures restricting movement outside of the home However sales in that week were still above the same week in 2019 and have remained above 2019 levels since100


40

Figure 12 Trend in food amp drink volume sales - Great Britain

Source PHE analysis of take home purchasing data from Kantar Worldpanel


41

Figure 13 shows the change in volume sales of categories of household items including food and beverages for 2020 year to date with the equivalent period for 2019100 Overall volume sales are up 115 for the same period last year but there are some differences by category Alcohol (up 296) has shown the largest increase followed by Savoury Home Cooking (up 264) Sweet Home Cooking (up 217) and Take Home Confectionery (up 197) As explained previously however some or all these increases may be due to food which was previously being consumed outside of the home in 2019 such as work and school lunches and snacks food and drink in restaurants cafes and pubs now being purchased for consumption at home since the lockdown restrictions were put in place Figure 13 Comparison of 2020 volume sales up to 28062020 with the same period 2019

Source PHE analysis of take home purchasing data from Kantar Worldpanel At a population level a recent survey (of gt2000 adults aged 16-75 years) reported changes in types of food people were eating When respondents were asked lsquoIn the last month have you done any of the following more or less oftenrsquo they reported that they were cooking food from scratch eating healthy foods and


42

snacking on cakes biscuits confectionery and savoury snacks more often (Figure 14)101 Figure 14 Changes in nutrition behaviour over the last month

Source Food Standards Agency and IPSOS Mori COVID-19 Consumer Tracker Waves 1 and 2 Base 2040 Online England Wales and NI adults 16-75 8-12 May 2020 The COVID-19 pandemic has had a contrasting effect on physical activity Interest in activity has never been higher102 and over 2 in 3 people saying it is important to exercise regularly100103 However actual activity levels appear to have gone down with a weekly survey of over 2000 people during April and May suggesting more people have been doing less physical activity than normal compared with those doing more (Figure 15)100104 It also appears that the pandemic has exacerbated inequalities including for adults with a disability long standing conditions or illness who were already more likely to be amongst the least active (Figure 16)100104


43

Figure 15 Trend in percentage of adults doing more or less physical activity than usual Survey Wave period 03042020ndash11052020

Source Survey into adult physical activity attitudes and behaviour Sport England by Savanta ComRes Figure 16 Percentage of adults doing more or less physical activity than usual by disability longstanding condition or illness pooled survey wave from 03042020-11052020

Source Survey into adult physical activity attitudes and behaviour Sport England by Savanta ComRes


44

Current action and how future action might look

Addressing obesity requires multiple action at national and local level including prevention and treatment Some of the policies and programmes such as the sugary drinks industry levy product reformulation and school food standards which are needed to contribute towards addressing obesity are set out in the governmentrsquos Childhood Obesity Plan(s)105 106 Advancing our Health prevention in the 2020s outlined additional opportunities on clearer food labelling improving the nutrient content of everyday food and drinks and the use of digital approaches to support for individuals to achieve and maintain a healthier weight and promote positive mental health107 During lockdown local authority and NHS commissioned behavioural weight management services which provide support to people wanting to change behaviour and achieve a healthier weight were either paused andor have adapted Ongoing research looking into how local approaches have adapted suggests that many services have continued to deliver using virtual and remote approaches Some early feedback from service users has reported that although some people miss the groups interactions for some the virtual approach is convenient and saves having to find childcare or transport to attend a meeting Supporting people who are living with excess weight to lose weight in a sustainable manner together with interventions to prevent weight gain across the population will plausibly reduce future population risks of COVID-19 Consideration as how to support modified services and to restart weight management services and provide such approaches including more intensive approaches at scale to support people living with obesity is required Further research is needed to understand the mechanisms involved regarding obesity and COVID-19 and the effect of weight loss on the severity of the infection Commitments in the NHS Long Term Plan include support for behavioural weight management services and this affords opportunity to better identify and offer support to people in communities that are facing a higher burden108 Positive changes to the environment as a response to COVID-19 include infrastructure to support more walking and cycling Whilst many local authorities are already working to support access to healthier food options there are opportunities to scale this up109 Despite having information on food purchases and physical activity changes during lockdown information is not available on dietary patterns or comparable population physical activity levels during this period It is also not clear what has


45

happened to weight status or the extent to which any changes during lockdown will be sustained There is no single solution to tackling obesity It is likely that many actions will be required to address this including ones that help prevention of excess weight gain by supporting healthier choices It is important that actions are sustained and include ones that impact on the population not just those who are more engaged in health PHE have already recommended a range of interventions to achieve this aim including limiting advertising and promotion of less healthy foods110 and promotion of active travel111 Improving access to weight management approaches including digital face to face and virtualremote options to the large numbers of people who could benefit and which are tailored to individual needs would also help address this national public health problem


46

9 Concluding remarks

The impact on health and life expectancy of excess weight has been known for years Evidence published during the pandemic despite its limitations consistently suggests that people with COVID-19 who are living with overweight or obesity are at notably increased risk of serious COVID-19 complications and death There are also several plausible mechanisms why excess body fat could worsen COVID-19 outcomes However at this time a more definitive conclusion on excess weight and the severity of COVID-19 cannot be made The UK has a relatively high prevalence of obesity compared with other countries It is currently unclear to what extent this may have contributed to the high incidence of COVID-19 seen so far in the UK compared with many other countries In addition it is uncertain to what extent differences in the prevalence of excess weight for different population groups (including for different ethnic groups and those living in deprived areas) explain the variation seen in COVID-19 risk across society Research on obesity and its association with COVID-19 adds to the evidence of the impacts on health vulnerability health outcomes inequalities and the demands on health and social care services of excess weight It is predicted that the numbers of people living with overweight or obesity are likely to increase Unless there is deep meaningful and sustained intervention to reduce the drivers on excess calorie intakes and low levels of physical activity the impact on health is likely to worsen For people living with obesity weight loss has been shown to bring health benefits There is currently no direct research of the effects of weight loss on COVID-19 risks However based on the putative mechanisms underpinning the associations it is reasonable to conclude that reducing excess weight could help reduce the risk of severe COVID-19 illness Moreover there is good evidence these interventions will bring wider health benefits to individuals and reduce pressures on the NHS due to overweight and obesity As the country looks to recover and live with COVID-19 the association between excess weight and severity of COVID-19 disease strengthens the case for long-term sustained action to address obesity There is however no single solution Multiple actions will be required to both prevent weight gain and offer treatment support to people who are living with overweight or obesity These actions need to change the environment we live in so making the healthier


47

options the easier option and unhealthier ones more difficult To achieve population level improvements and not widen health disparities structural drivers of excess calorie intakes and low levels of physical activity will need to be tackled More targeted actions are needed to support change in groups disproportionately affected by obesity and its causes including people in the countryrsquos most deprived socio-economic groups Excess weight may be one of the few modifiable risk factors for COVID-19 where there is extant evidence of interventions that are effective Other factors such as age and ethnicity cannot be changed and factors such as deprivation are complex to address Supporting people who are living with overweight or obesity to lose weight together with interventions to prevent weight gain across the population will plausibly reduce future population risks of COVID-19 Rapid development of research relating to obesity and COVID-19 and its outputs have been vital in supporting policy and decision makers It is however clear that there is much more to understand when it comes to obesity and the mechanisms that may be involved and interact with the pathogenesis of COVID-19 What puts some groups more at risk and what effect achieving a healthier weight and weight loss might have are key questions to explore PHE will continue to monitor evidence as it emerges on excess weight and COVID-19 and encourages more research in the area and more evidence syntheses


48

Appendix 1 Summary information on study design of UK studies

Docherty et al Hamer et al Ho et al Khawaja et al Aim(s) of study

To characterize the clinical features of patients with severe COVID-19 in the UK

General population study on lifestyle risk factors (including obesity) on COVID-19

To investigate demographic lifestyle socio-economic and clinical risk factors comparing them to risk factors for pneumonia and influenza

To identify the sociodemographic lifestyle comorbidity and antihypertensive medication associations with the development of hospitalisation with COVID-19 in an English population

Study description (type amp data source and key methods)

Prospective observational cohort study with rapid data gathering and near real time analysis using a pre-approved questionnaire adopted by the WHO

UK Biobank study Prospective cohort data with national registry linkage to hospitalisation

UK Biobank study UK Biobank study Prospective cohort study

Assessment of BMI (measured htwt records etc)

Obesity identified as recognised by clinical staff Height and weight was not measured

BMI was calculated from measured height and weight at baseline between 2006 and 2010




49

Docherty et al Hamer et al Ho et al Khawaja et al Sample size (total) and period of data collection (2020)

n= 20133 6 February-19 April

n= 387109 n=760 (positive COVID-19 cases) 16 March-26 April

n=428225 n=340 (positive result in hospital) 16 March-14 April

n=406793 n=605 cases (positive test for COVID-19) 16 March-16 April

Factors adjustedcontrolled

The association of age with in-hospital mortality was assessed adjusting for pre-existing patient characteristics (sex and comorbidities - including obesity)

Adjustments for age sex smoking physical activity excessive alcohol intake education ethnicity diabetes hypertension and cardiovascular disease

Adjustments for Age sex ethnicity SES long-standing illness high cystatin C (non-modifiable factors) BMI smoking slow walking pace use of blood pressure medications (modifiable factors)

Examined all comorbidities together in a multivariable model Adjusted for sex ethnicity BMI smoking hypertension and chronic obstructive pulmonary disease

Peer reviewed (as at 18 July 2020)

Certified by peer review Certified by peer review Not certified by peer review

Not certified by peer review

Limitations Height and weight not measured Data on BMI characteristics not reported The questionnaire identified patients with obesity as recognised by clinical staff

Not representative of UK population




50

Perez-Guzman et al Prats-Uribe et al Razieh et al Holman et al Aim(s) of study

1Describe baseline characteristics and outcomes for patients hospitalised with laboratory confirmed SARS-CoV-2 infection in hospital since the start of the pandemic 2 Evaluate demographic and clinical factors associated with outcomes 3 Evaluate the proportion of patients hospitalised for COVID-19 from BAME groups and evaluate whether ethnicity is associated with different outcomes

To study the association between ethnicity and risk of COVID-19 and adjust it by deprivation and previous comorbidity

Adjusted logistic regression to 1 quantify the association of BMI with the risk of a positive test for COVID-19 stratified by ethnic group 2 investigate whether the odds of COVID-19 in BME (South Asian (SA) and Black African or Caribbean (BAC) individuals relative to White Europeans (WEs) varied by BMI level

To investigate the relationship between hyperglycaemia and other modifiable risk factors including obesity and risk of COVID-19 related mortality in both community and hospital environments


A retrospective cohort study on all patients hospitalised with laboratory-confirmed SARS-CoV-2 infection at Imperial College Healthcare NHS Trust

UK Biobank study Prospective cohort study Linked to HES and COVID-19 tests

UK Biobank study linked to national COVID-19 laboratory test data through PHE

National Diabetes Audit and General Practice Extraction Service - supplemented by data submitted by specialist diabetes services


51

Perez-Guzman et al Prats-Uribe et al Razieh et al Holman et al Cox proportional hazards analysis investigated the relationship between risk factors and COVID-19 related death in a cohort alive on 16 February 2020 and followed to 11 May 2020


50 of admissions had BMI data missing Authors commented that this might relate to the severity of disease on admission

BMI was calculated from measured height and weight at baseline between March 2006 and July 2010


BMI was identified using the latest recorded measurement between 1 January 2017 and 31 December 2019

Sample size (total) and period of data collection (2020)

n=520 25 February-5 April

n=415582 16 March-14 April

n=5623 unique test results 16 March-14 June

The cohort analysis included n=264390 people with Type 1 diabetes and n=2874020 people with Type 2 diabetes


Adjusted for age sex and admission hypoxia thrombocytopenia renal failure hypoalbuminaemia and ethnicity

Adjusted for age sex alcohol drinking and smoking

Adjusted for age at test sex social deprivation (Townsend score) smoking status cancer illnesses and non-cancer illnesses systolic blood

Adjusted for sex age deprivation region ethnic group HbA1c duration of diagnosis eGFR BMI smoking co-morbidities


52

Perez-Guzman et al Prats-Uribe et al Razieh et al Holman et al pressure HDL cholesterol total cholesterol and HbA1c

(previous stroke previous heart failure


Unable to determine Imperial College report

Not certified by peer review Certified by peer review Not certified by peer review

Limitations 50 of admissions had BMI data missing



The higher risk seen in people with lower BMI could be linked unmeasured confounding or residual confounding

Williamson et al (2020) Yates et al (2020) Hippisley-Cox et al (2020)

Sattar et al (2020)

Aim(s) of study

To determine factors associated with risk of death from COVID-19 in England

Obesity and risk of COVID-19 analysis of UK Biobank Hypothesis BMI and waist circumference are independently associated with COVID-19

Whether patients prescribed angiotensin converting enzyme inhibitor (ACE inhibitor) and angiotensin receptor blocker (ARB) drugs associated with differential risks of contracting severe COVID-19 disease and receiving associated ICU admission

To examine the link between BMI and risk of a positive test for SARS-CoV-2 and risk of COVID-19-related death among UK Biobank participants


53


Sattar et al (2020)


OpenSAFELY A cohort study using national primary care electronic health record data linked to in-hospital COVID-19 death data - COVID-19 Patient Notification System (CPNS) from NHSEX and Office for National Statistics

Investigation between obesity and laboratory confirmed COVID-19 (UK Biobank)

A large open cohort study of all patients aged 20-99 registered with 1205 general practices in England contributing to the QResearch database linked to COVID-19 Real-time Polymerase Chain Reaction test records and with IC records

Used UK Biobank data to examine the association between BMI and test positivity for SARS-CoV-2 infection in hospital as well as COVID-19 related deaths


BMI was ascertained from weight measurements within the last 10 years restricted to those taken when the patient was over 16 years old


BMI taken from the latest information recorded in the GP record



n=17278392 adults 1 February-25 April 2020

n= 2494 unique test results available 16 March-3 May 2020

n=8middot28 million participants n=19486 patients who had COVID-19 disease n=1286 received ICU care 1 January-27 April 2020

n=374503 n=4855 participants tested for SARS-CoV-2 in hospital n=839 tested positive and n=189 of these individuals died from COVID-19 16 March-31 May 2020


Adjusted for age sex BMI smoking index of multiple deprivation quintile and comorbidities

Model 1 unadjusted Model 2 adjusted for age sex ethnicity social deprivation [Townsend

Adjusted for age sex deprivation ethnicity geographical region smoking concurrent

Models were adjusted for age SES (Townsend Index) ethnicity smoking (current former never) alcohol intake


54


Sattar et al (2020)

index] cancer illnesses [number] non-cancer illnesses [number] treatmentsmedications undertaken [number] systolic blood pressure and household density [number per house] Model 3 adjusted for Model 2 plus smoking status [never past current] walking pace [slow steady average brisk] leisure time physical activity [METminutesweek] fruit and vegetable consumption [portions per week] red meat consumption [portions per week] and alcohol intake [unitsday]

morbidity and long term medication

(unitweek) and baseline cardiovascular disease and diabetes


Certified by peer review Letter to editor Certified by peer review Certified by peer review

Limitations Not representative of UK population Some possible misclassification of COVID-19 positive cases and some misclassification of deaths resulting from COVID-19


Exposure to medication class of drug bias relating to laboratory confirmed cases false negative tests for COVID-19 selection bias for those submitted to

Only a small proportion of overall UK Biobank participants were tested for SARS-CoV-2 total numbers of deaths were modest those untested as


55


Sattar et al (2020)

hospital or ICU ICU deaths were not included in the analysis

well as those tested negative were grouped together in the analysis baseline anthropometric measures were collected a median of 109 (IQR 97e124) years before SARS-CoV-2 testing was conducted However baseline BMI values reliably estimate BMI variance Race crudely categorised as White and non-White individuals with higher weights may have had greater exposure to the virus


56

References

1 National Institute for Health and Care Excellence (2014) Clinical Guideline 189 Obesity identification assessment and management Available at httpswwwniceorgukguidancecg189 [accessed 16 July 2020] 2 National Institute for Health and Care Excellence (2013) BMI preventing ill health and premature death in black Asian and other minority ethnic groups Public Health Guideline 46 Available at httpswwwniceorgukguidanceph46chapter1-recommendations [accessed 16 July 2020] 3 Newton JN Briggs AD Murray CJ Dicker D Foreman KJ Wang H Naghavi M Forouzanfar MH Ohno SL Barber RM Vos T Changes in health in England with analysis by English regions and areas of deprivation 1990ndash2013 a systematic analysis for the Global Burden of Disease Study 2013 The Lancet 2015 Dec 5386(10010)2257-74 4 World Health Organization (2016) Obesity and overweight Factsheet No 311 Available at wwwwhointmediacentrefactsheetsfs311en [accessed 16 July 2020] 5 Williams R Aspinall R Bellis M Camps-Walsh G Cramp M Dhawan A Ferguson J Forton D Foster G Gilmore I Hickman M Hudson M Kelly D Langford A Lombard M Longworth L Martin N Moriarty K Newsome P OGrady J Pryke R Rutter H Ryder S Sheron N Smith T Addressing liver disease in the UK a blueprint for attaining excellence in health care and reducing premature mortality from lifestyle issues of excess consumption of alcohol obesity and viral hepatitis Lancet 2014 Nov 29384(9958)1953-97 Available at httpspubmedncbinlmnihgov25433429 [accessed 16 July 2020] 6 National Institute for Health and Care Excellence (2016) Non-alcoholic fatty liver disease assessment and management NICE guideline NG49 methods evidence and recommendations Available at httpswwwniceorgukguidanceng49 [accessed 16 July 2020] 7 World Health Organization (2020) WHO announces COVID-19 outbreak a pandemic Available athttpswwweurowhointenhealth-topicshealth-emergenciescoronavirus-covid-19newsnews20203who-announces-covid-19-outbreak-a-pandemic [accessed 16 July 2020] 8 HM Government (2020) Coronavirus (COVID-19) in the UK ndash Dashboard Available at httpscoronavirusdatagovuk_ga=2790323489213518621594630825-993850391583745948 [accessed 16 July 2020] 9 HM Government (2020) Staying alert and safe (social distancing) Clinically Vulnerable People Available at httpswwwgovukgovernmentpublicationsstaying-alert-and-safe-social-distancingstaying-alert-and-safe-social-distancing-after-4-julyclinically-vulnerable-people [accessed 16 July 2020]


57

10 Public Health England (2020) Disparities in the risk and outcomes of COVID-19 Available at httpswwwgovukgovernmentpublicationsCOVID-19-review-of-disparities-in-risks-and-outcomes [accessed 16 July 2020] 11 NHS Digital (2018) Health Survey for England Available at httpswwwgovukgovernmentstatisticshealth-survey-for-england-2018 [accessed 16 July 2020] 12 Health Profile for England(2020) Available at httpswwwgovukgovernmentpublicationshealth-profile-for-england-2019 [accessed 3 July 2020] 13 Organisation for Economic Co-operation and Development Available at httpswwwoecdorghealthobesity-updatehtm [accessed 3 July 2020] 14 The GBD 2015 Obesity Collaborators (2017) Health Effects of Overweight and Obesity in 195 Countries over 25 Years Available at httpswwwnejmorgdoifull101056NEJMoa1614362 [accessed 16 July 2020] 15 Bhaskaran K Dos-Santos-Silva I Leon DA Douglas IJ Smeeth L Association of BMI with overall and cause-specific mortality a population-based cohort study of 36 million adults in the UK Lancet Diabetes Endocrinol 2018 6 944ndash53 Available at httpswwwthelancetcomactionshowPdfpii=S2213-858728182930288-2 [accessed 16 July 2020] 16 Cancer Research UK (2018) Does obesity cause cancer Available at httpswwwcancerresearchukorgabout-cancercauses-of-cancerobesity-weight-and-cancerdoes-obesity-cause-cancerObesityrefs0 [accessed 16 July 2020] 17 Garg S Kim L Whitaker M et al Hospitalization Rates and Characteristics of Patients Hospitalized with Laboratory-Confirmed Coronavirus Disease 2019 mdash COVID-NET 14 States March 1ndash30 2020 MMWR Morb Mortal Wkly Rep 202069458ndash464 httpswwwcdcgovmmwrvolumes69wrmm6915e3htm 18 Public Health England (2019) Guidance Musculoskeletal Health applying All Our Health Available at httpswwwgovukgovernmentpublicationsmusculoskeletal-health-applying-all-our-healthmusculoskeletal-health-applying-all-our-health [accessed 16 July 2020] 19 The Information Centre (2006) Lifestyles Statistics Statistics on Obesity Physical Activity and Diet England Available at httpsfilesdigitalnhsukpublicationimportpub00xxxpub00166obes-phys-acti-diet-eng-2006-reppdf [accessed 16 July 2020] 20 Public Health England and NHS Right Care (2019) The 2nd Atlas of variation in risk factors and healthcare for respiratory disease in England Reducing unwarranted variation to improve health outcomes and value Available at httpsfingertipspheorgukstatic-reportsatlas-of-variation2ndRespiratoryAtlas_v10_20190923pdf [accessed 16 July 2020]


58

21 Luppino FS de Wit LM Bouvy PF Stijnen T Cuijpers P Penninx BW Zitman FG Overweight obesity and depression a systematic review and meta-analysis of longitudinal studies Archives of general psychiatry 2010 Mar 167(3)220-9 22 NHS Digital (2020) Statistics on Obesity Physical Activity and Diet England 2020 Available at httpsdigitalnhsukdata-and-informationpublicationsstatisticalstatistics-on-obesity-physical-activity-and-dietengland-2020part-3-adult-obesity-copy [accessed 16 July 2020] 23 NHS Digital (2018) Health Survey for England Available at httpsdigitalnhsukdata-and-informationpublicationsstatisticalhealth-survey-for-england2018 [accessed 16 July 2020] 24 Public Health England (2020) Beyond the data Understanding the impact of COVID-19 on BAME groups httpsassetspublishingservicegovukgovernmentuploadssystemuploadsattachment_datafile892376COVID_stakeholder_engagement_synthesis_beyond_the_datapdf [accessed 21 July 2020] 25 Niedzwiedz CL OrsquoDonnell CA Jani BD Demou E Ho FK Celis-Morales C Nicholl BI Mair FS Welsh P Sattar N Pell JP Ethnic and socioeconomic differences in SARS-CoV-2 infection prospective cohort study using UK Biobank BMC medicine 2020 Dec181-4 26 Abdellaoui A Regional differences in reported COVID-19 cases show genetic correlations with higher socio-economic status and better health potentially confounding studies on the genetics of disease susceptibility Available at httpswwwmedrxivorgcontent1011012020042420075333v1 [accessed 16 July 2020] 27 NHS Digital (2017) Health Survey for England Available at httpsdigitalnhsukdata-and-informationpublicationsstatisticalhealth-survey-for-england2017 [accessed 16 July 2020] 28 Lassale C Gaye B Hamer M Gale CR Batty GD Ethnic Disparities in Hospitalisation for COVID-19 in England The Role of Socioeconomic Factors Mental Health and Inflammatory and Pro-inflammatory Factors in a Community-based Cohort Study Brain Behavior and Immunity 2020 Jun 1 8844-49 doi 101016jbbi202005074 [accessed 16 July 2020] 29 Public Health England (2018) Severe mental illness and physical health inequalities Briefing [online] HM Government Available at httpswwwgovukgovernmentpublicationssevere-mental-illness-smi-physical-health-inequalitiessevere-mental-illness-and-physical-health-inequalities-briefing [accessed 16 July 2020] 30 Public Health England (2020) Guidance Obesity and weight management for people with learning disabilities Available at


59

httpswwwgovukgovernmentpublicationsobesity-weight-management-and-people-with-learning-disabilitiesobesity-and-weight-management-for-people-with-learning-disabilities-guidance [accessed 16 July 2020] 31 UK Biobank [Internet] Access matter representativeness of the UK Biobank resource Available at httpwwwukbiobankacukwp-contentuploads201703access-matters-representativenesspdf [accessed 16 July 2020] 32 Yang J Hu J Zhu C Obesity aggravates COVID‐19 a systematic review and meta‐analysis 2020 J Med Virol httpsdoiabs101002jmv26237 [accessed 16 July 2020] 33 Hussain A Mahawar K Xia Z Yang W El-Hasani S Obesity and mortality of COVID-19 Meta-analysis Obes Res Clin Pract 2020 httpovidspovidcomovidwebcgiT=JSampPAGE=referenceampD=medpampNEWS=NampAN=32660813 [accessed 16 July 2020] 34 Yates T Razieh C Zaccardi F Davies MJ Khunti K Obesity and risk of COVID-19 analysis of UK Biobank Primary Care Diabetes 2020 May 27 Available at httpsdoiorg101016jpcd202005011 [accessed 16 July 2020] 35 Hamer M Kivimaumlki M Gale CR Batty GD Lifestyle risk factors inflammatory mechanisms and COVID-19 hospitalization A community-based cohort study of 387109 adults in UK Brain Behav Immun 2020 Jul87184-187 Available at httpsdoiorg101016jbbi202005059 [accessed 16 July] 36 Khawaja AP Warwick AN Hysi PG Kastner A Dick A Khaw PT Tufail A Foster PJ Khaw KT Associations with COVID-19 hospitalisation amongst 406793 adults the UK Biobank prospective cohort study 2020 Jan 1 Available at httpsdoiorg1011012020050620092957 [accessed 16 July 2020] 37 Ho FK Celis-Morales CA Gray SR Katikireddi SV Niedzwiedz CL Hastie C Lyall DM Ferguson LD Berry C Mackay DF Gill JM Modifiable and non-modifiable risk factors for COVID-19 results from UK Biobank medRxiv 2020 Jan 1 Available at httpsdoiorg1011012020042820083295 [accessed 16 July] 38 Razieh C Zaccardi F Davies MJ Khunti K Yates T Body mass index and the risk of COVID-19 across ethnic groups Analysis of UK Biobank Diabetes Obes Metab 2020 Jun 29101111dom14125 doi 101111dom14125 Epub ahead of print PMID 32602268 PMCID PMC7362044 [accessed 16 July] 39 Prats-Uribe A Paredes R Prieto-Alhambra D Ethnicity comorbidity socioeconomic status and their associations with COVID-19 infection in England a cohort analysis of UK Biobank data medRxiv 2020 Jan 1 Available at httpswwwmedrxivorgcontent1011012020050620092676v3 [accessed 16 July] 40 Sattar N Ho FK Gill JM Ghouri N Gray SR Celis-Morales CA Katikireddi SV Berry C Pell JP McMurray JJ Welsh P BMI and future risk for COVID-19 infection and death across sex age and ethnicity preliminary findings from UK biobank Diabetes amp


60

Metabolic Syndrome Clinical Research amp Reviews 2020 Jun 30 Available at httpsdoiorg101016jdsx202006060 [accessed 16 July]

41 Docherty AB Harrison EM Green CA Hardwick HE Pius R Norman L Holden KA Read JM Dondelinger F Carson G Merson L ISARIC4C investigators Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol prospective observational cohort study BMJ 2020 May 22369m1985 doi 101136bmjm1985 PMID 32444460 PMCID PMC7243036 [accessed 16 July] 42 Perez Guzman PN Daunt A Mukherjee S Crook P Forlano R Kont M Lochen A Vollmer M Middleton P Judge R Harlow C Report 17 Clinical characteristics and predictors of outcomes of hospitalised patients with COVID-19 in a London NHS Trust a retrospective cohort study Available at httpsdoiorg102556178613 [accessed 16 July] 43 Hippisley-Cox et al Risk of Severe COVID-19 Disease with ACE inhibitors and Angiotensin Receptor Blockers including 8middot3 Million People (in press) 44 Williamson E Walker AJ Bhaskaran KJ Bacon S Bates C Morton CE Curtis HJ Mehrkar A Evans D Inglesby P Cockburn J OpenSAFELY factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients MedRxiv 2020 Jan 1Available at httpswwwmedrxivorgcontent1011012020050620092999v1 [accessed 16 July 2020] 45 Williamson EJ Walker AJ Bhaskaran K Bacon S Bates C Morton CE Curtis HJ Mehrkar A Evans D Inglesby P Cockburn J OpenSAFELY factors associated with COVID-19 death in 17 million patients Nature 2020 Jul 81-1 Available at httpspubmedncbinlmnihgov32640463 [accessed 16 July 2020] 46 Holman N Knighton P Kar P OrsquoKeefe J Curley M Weaver A Barron E Bakhai C Khunti K Wareham NJ Sattar N Type 1 and Type 2 diabetes and COVID-19 related mortality in England a cohort study in people with diabetes The Lancet Diabetes amp Endocrinology (in press)

47 Intensive Care National Audit and Research Centre ICNARC report on COVID-19 in Critical Care 2020 Available at httpswwwicnarcorgOur-AuditAuditsCmpReports [Accessed 16 July 2020] 48 Simonnet A Chetboun M Poissy J Raverdy V Noulette J Duhamel A Labreuche J Mathieu D Pattou F Jourdain M LICORN and the Lille COVID‐19 and Obesity study group High prevalence of obesity in severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) requiring invasive mechanical ventilation Obesity 2020 Apr 9 Available at httpsonlinelibrarywileycomdoiabs101002oby22831 [accessed 16 July 2020] 49 Qingxian C Fengjuan C Fang L Obesity and COVID-19 severity in a designated hospital in Shenzhen China 2020 httpdxdoiorg102139ssrn3556658 [accessed 16 July 2020]


61

50 Busetto L Bettini S Fabris R Serra R Dal Prarsquo C Maffei P Rossato M Fioretto P Vettor R Obesity and COVID‐19 an Italian snapshot Obesity 2020 May 28 Available at httpsdoiorg101002oby22918 [accessed 16 July 2020] 51 Gao F Zheng I Wang XB Sun QF Pan KH Wang TY Chen YP Obesity Is a Risk Factor for Greater COVID-19 Severity Diabetes Care 2020 Jul43(7)e72-e74 Available at httpscarediabetesjournalsorgcontent437e72 [accessed 16 July 2020] 52 Kalligeros M Shehadeh F Mylona EK Benitez G Beckwith CG Chan PA Mylonakis E Association of Obesity with Disease Severity among Patients with COVID-19 Obesity (Silver Spring Md) 2020 Apr 30 Available at httpsonlinelibrarywileycomdoipdf101002oby22859 [accessed 16 July 2020] 53 Kass DA Duggal P Cingolani O Obesity could shift severe Covid-19 disease to younger ages The Lancet 2020 3951544 Available at httpswwwthelancetcompdfsjournalslancetPIIS0140-6736(20)31024-2pdf [accessed 16 July 2020] 54 Bhasin A Nam H Yeh C Lee J Liebovitz D Achenbach C Is BMI higher in younger patients with COVID‐19 Association between BMI and COVID‐19 hospitalization by age Obesity 2020 Jul 1 Available at httpsdoiorg101002oby22947 [accessed 16 July 2020] 55 Moriconi D Masi S Rebelos E Virdis A Manca ML De Marco S Taddei S Nannipieri M Obesity prolongs the hospital stay in patients affected by COVID-19 and may impact on SARS-COV-2 shedding Obesity Research amp Clinical Practice 2020 Jun 4 Available at httpsdoiorg101016jorcp202005009 [accessed 16 July 2020] 56 Chen Q Zheng Z Zhang C Zhang X Wu H Wang J Wang S Zheng C Clinical characteristics of 145 patients with corona virus disease 2019 (COVID-19) in Taizhou Zhejiang China Infection 2020 Apr 281-9 Available at httpsdoiorg101007s15010-020-01432-5 [accessed 16 July 2020] 57 Caussy C Pattou F Wallet F Simon C Chalopin S Telliam C Mathieu D Subtil F Frobert E Alligier M Delaunay D Prevalence of obesity among adult inpatients with COVID-19 in France The Lancet Diabetes amp Endocrinology 2020 Jul 18(7)562-4 Available at httpspubmedncbinlmnihgov32437642 [accessed 16 July 2020] 58 Suleyman G Fadel RA Malette KM Hammond C Abdulla H Entz A Demertzis Z Hanna Z Failla A Dagher C Chaudhry Z Clinical characteristics and morbidity associated with coronavirus disease 2019 in a series of patients in metropolitan detroit JAMA network open 2020 Jun 13(6)e2012270 Available at httpsjamanetworkcomjournalsjamanetworkopenfullarticle2767216 [accessed 16 July 2020] 59 Pettit NN MacKenzie EL Ridgway J Pursell K Ash D Patel B Pho MT Obesity is Associated with Increased Risk for Mortality Among Hospitalized Patients with COVID‐


62

19 Obesity 2020 Jun 26 Available at httpsdoiorg101002oby22941 [accessed 16 July 2020] 60 Lighter J Phillips M Hochman S Obesity in patients younger than 60 years is a risk factor for COVID-19 hospital admission [published online April 9 2020] Clin Infect Dis Available at httpsdoiorg101093cidciaa415 [accessed 16 July 2020] 61 Petrilli CM Jones SA Yang J Rajagopalan H ODonnell LF Chernyak Y Tobin K Cerfolio RJ Francois F Horwitz LI Factors associated with hospitalization and critical illness among 4103 patients with COVID-19 disease in New York City MedRxiv 2020 Jan 1 Available at httpswwwmedrxivorgcontent1011012020040820057794v1 [accessed 16 July 2020] 62 Argenziano MG Bruce SL Slater CL Tiao JR Baldwin MR Barr RG Chang BP Chau KH Choi JJ Gavin N Goyal P Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York retrospective case series bmj 2020 May 29369 Available at httpswwwbmjcomcontent369bmjm1996 [accessed 16 July 2020] 63 Klang E Kassim G Soffer S Freeman R Levin MA Reich DL Morbid Obesity as an Independent Risk Factor for COVID‐19 Mortality in Hospitalized Patients Younger than 50 Obesity 2020 May 23 Available at httpsonlinelibrarywileycomdoiepdf101002oby22913 [accessed 16 July 2020] 64 Denova‐Gutieacuterrez E Lopez‐Gatell H Alomia‐Zegarra JL Loacutepez‐Ridaura R Zaragoza‐Jimenez CA Dyer‐Leal DD Corteacutes‐Alcala R Villa‐Reyes T Gutieacuterrez‐Vargas R Rodriacuteguez‐Gonzaacutelez K Escondrillas‐Maya C The association between obesity type 2 diabetes and hypertension with severe COVID‐19 on admission among Mexicans Obesity 2020 Jul 1 httpsdoi101002oby22946 65 Bello-Chavolla OY Gonzaacutelez-Diacuteaz A Antonio-Villa NE Fermiacuten-Martiacutenez CA Maacuterquez-Salinas A Vargas-Vaacutezquez A Bahena-Loacutepez JP Garciacutea-Pentildea C Aguilar-Salinas CA Gutieacuterrez-Robledo LM Unequal impact of structural health determinants and comorbidity on COVID-19 severity and lethality in older Mexican adults Looking beyond chronological aging medRxiv 2020 Jan 1 Available at httpsdoiorg101093geronaglaa163 [accessed 16 July 2020] 66 Bello-Chavolla OY Bahena-Lopez JP Antonio-Villa NE Vargas-Vaacutezquez A Gonzaacutelez-Diacuteaz A Maacuterquez-Salinas A Fermiacuten-Martiacutenez CA Naveja JJ Aguilar-Salinas CA Predicting mortality due to SARS-CoV-2 A mechanistic score relating obesity and diabetes to COVID-19 outcomes in Mexico medRxiv 2020 Jan 1 Available at httpsdoiorg101210clinemdgaa346 [accessed 16 July 2020] 67 Honce R Schultz-Cherry S Impact of obesity on influenza A virus pathogenesis immune response and evolution Frontiers in immunology 2019 May 10101071 Available at httpsdoiorg103389fimmu201901071 [accessed 16 July 2020] 68 Green WD Beck MA Obesity impairs the adaptive immune response to influenza virus Annals of the American Thoracic Society 2017 Nov14(Supplement 5)S406-9


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64

78 National Institute for Health and Care Excellence (2014) Weight management lifestyle services for overweight or obese adults London NICE Public Health Guidance [PH53] Available at httpswwwniceorgukguidanceph53chapter1-Recommendations [accessed 17 July 2020] 79 Scottish Intercollegiate Guidelines Network (2010) Management of Obesity Available at httpswwwsignacukassetssign115pdf [accessed 16 July 2020]

80 Hamman RF Wing RR Edelstein SL Lachin JM Bray GA Delahanty L Hoskin M Kriska AM Mayer-Davis EJ Pi-Sunyer X Regensteiner J Effect of weight loss with lifestyle intervention on risk of diabetes Diabetes care 2006 Sep 129(9)2102-7 Available at httpscarediabetesjournalsorgcontent2992102 [accessed 16 July 2020]

81 Magkos F Fraterrigo G Yoshino J Luecking C Kirbach K Kelly SC De Las Fuentes L He S Okunade AL Patterson BW Klein S Effects of moderate and subsequent progressive weight loss on metabolic function and adipose tissue biology in humans with obesity Cell metabolism 2016 Apr 1223(4)591-601 Available at httpsdoiorg101016jcmet201602005 [accessed 16 July 2020] 82 Lean ME Leslie WS Barnes AC Brosnahan N Thom G McCombie L Peters C Zhyzhneuskaya S Al-Mrabeh A Hollingsworth KG Rodrigues AM Durability of a primary care-led weight-management intervention for remission of type 2 diabetes 2-year results of the DiRECT open-label cluster-randomised trial The Lancet Diabetes amp Endocrinology 2019 May 17(5)344-55 83 Astbury NM Aveyard P Nickless A Hood K Corfield K Lowe R Jebb SA Doctor Referral of Overweight People to Low Energy total diet replacement Treatment (DROPLET) pragmatic randomised controlled trial BMJ 2018 Sep 26362k3760 84 Aminian A Zajichek A Arterburn DE Wolski KE Brethauer SA Schauer PR Kattan MW Nissen SE Association of metabolic surgery with major adverse cardiovascular outcomes in patients with type 2 diabetes and obesity Jama 2019 Oct 1322(13)1271-82

85 Wing RR Lang W Wadden TA Safford M Knowler WC Bertoni AG Hill JO Brancati FL Peters A Wagenknecht L Look AHEAD Research Group Benefits of modest weight loss in improving cardiovascular risk factors in overweight and obese individuals with type 2 diabetes Diabetes care 2011 Jul 134(7)1481-6 Available at httpspubmedncbinlmnihgov21593294 [accessed 16 July 2020]

86 Siebenhofer A Jeitler K Berghold A Waltering A Hemkens LG Semlitsch T Pachler C Strametz R Horvath K Long‐term effects of weight‐reducing diets in hypertensive patients Cochrane Database of Systematic Reviews 2011 Issue 9 Art No CD008274 DOI 10100214651858CD008274pub2 87 Look AHEAD Research Group Association of the magnitude of weight loss and changes in physical fitness with long-term cardiovascular disease outcomes in overweight or obese people with type 2 diabetes a post-hoc analysis of the Look


65

AHEAD randomised clinical trial The lancet Diabetes amp endocrinology 2016 Nov 14(11)913-21 88 Lasikiewicz N Myrissa K Hoyland A Lawton CL Psychological benefits of weight loss following behavioural andor dietary weight loss interventions A systematic research review Appetite 2014 Jan 172123-37 Available at httpdxdoiorg101016jappet201309017 [accessed 16 July 2020] 89 Faulconbridge LF Wadden TA Rubin RR Wing RR Walkup MP Fabricatore AN Coday M Van Dorsten B Mount DL Ewing LJ Look AHEAD Research Group One‐year changes in symptoms of depression and weight in overweightobese individuals with type 2 diabetes in the look AHEAD study Obesity 2012 Apr20(4)783-93 Available at httpswwwncbinlmnihgovpmcarticlesPMC3298842 [accessed 16 July 2020] 90 Rejeski WJ Ip EH Bertoni AG Bray GA Evans G Gregg EW Zhang Q Lifestyle change and mobility in obese adults with type 2 diabetes New England Journal of Medicine 2012 Mar 29366(13)1209-17 91 Larsson SC Baumlck M Rees JM Mason AM Burgess S Body mass index and body composition in relation to 14 cardiovascular conditions in UK Biobank a Mendelian randomization study European Heart Journal 2020 Jan 741(2)221-6 Available at httpspubmedncbinlmnihgov31195408 [accessed 16 July 2020] 92 Liakopoulos V Franzeacuten S Svensson AM Sattar N Miftaraj M Bjoumlrck S Ottosson J Naumlslund I Gudbjoumlrnsdottir S Eliasson B Renal and Cardiovascular Outcomes After Weight Loss From Gastric Bypass Surgery in Type 2 Diabetes Cardiorenal Risk Reductions Exceed Atherosclerotic Benefits Diabetes Care 2020 Jun43(6)1276-1284 doi 102337dc19-1703 Epub 2020 Mar 9 PMID 32152136 93 Public Health England (2018) Calorie reduction the scope and ambition for action Available at httpsassetspublishingservicegovukgovernmentuploadssystemuploadsattachment_datafile800675Calories_Evidence_Documentpdf [accessed 16 July 2020] 94 Foresight Report (2007) Tackling Obesities Future Choices ndash Project Report 2nd Edition Government Office for Sciene London Available at httpsassetspublishingservicegovukgovernmentuploadssystemuploadsattachment_datafile28793707-1184x-tackling-obesities-future-choices-reportpdf [accessed 16 July 2020] 95 Public Health England (2019) National Diet and Nutrition Survey years 7amp8 (201415-1516) dataset UK Data Service Available at httpdoiorg105255UKDA-SN-6533-15 [accessed 16 July 2020] 96 Business Matters [Internet] (2020) Is the food delivery industry still on the rise Available at httpswwwbmmagazinecoukbusinessis-the-food-delivery-industry-still-on-the-rise [accessed 16 July 2020]


66

97 NHS Digital (2020) National Child Measurement Programme Available at httpsdigitalnhsukservicesnational-child-measurement-programme [accessed 16 July 2020] 98 Public Health England (2018) Englandrsquos poorest areas are fast food hotspots Available at httpswwwgovukgovernmentnewsenglands-poorest-areas-are-fast-food-hotspots [accessed 16 July 2020] 99 Office for National Statistics (2020) One in eight British households has no garden Available at httpswwwonsgovukeconomyenvironmentalaccountsarticlesoneineightbritishhouseholdshasnogardenlatest [accessed 16 July 2020] 100 Public Health England (2020) Wider impacts of COVID-19 on health Available at httpsanalyticsphegovukappscovid-19-indirect-effects [accessed 16 July 2020] 101 Food Standards Agency (2020) COVID-19 Consumer Tracker Waves 1 and 2 Available at httpswwwfoodgovuksitesdefaultfilesmediadocumentcovid-19-consumer-tracker-reportpdf [accessed 16 July 2020] 102 Ding D del Pozo Cruz B Green MA Bauman AE Is the COVID-19 lockdown nudging people to be more active a big data analysis British Journal of Sports Medicine 2020 June 30 doi 101136bjsports-2020-102575 [accessed 16 July 2020] 103 Sport England Savanta ComRes (2020) Survey into adult physical activity attitudes and behaviour Waves 1-10 Available at httpswwwsportenglandorgknow-your-audiencedemographic-knowledgecoronavirusthe_story_so_far [accessed 16 July 2020] 104 Sport England Savanta ComRes (2020) Physical Activity Attitudes and Behaviours Savanta ComRes Waves 1-6 Available at httpsanalyticsphegovukappscovid-19-indirect-effects [accessed 16 July 2020] 105 HM Government (2016) Childhood obesity a plan for action Available at wwwgovukgovernmentpublicationschildhood-obesity-a-plan-for-action [accessed 16 July 2020] 106 HM Government (2018) Childhood obesity a plan for action chapter 2 Available at wwwgovukgovernmentpublicationschildhood-obesity-a-plan-for-action-chapter-2 [accessed 16 July 2020] 107 Department for Health and Social Care (2019) Advancing our Health Available at httpswwwgovukgovernmentconsultationsadvancing-our-health-prevention-in-the-2020s [accessed 16 July 2020] 108 NHS (2019) Long Term Plan Available at httpswwwlongtermplannhsuk [accessed 16 July 2020]


67

109 Public Health England (2020) Using the planning system to promote healthy weight environments Guidance and supplementary planning document template for local authority public health and planning teams Available at httpswwwgovukgovernmentpublicationshealthy-weight-environments-using-the-planning-system [accessed 16 July 2020] 110 Public Health England (2015) Sugar Reduction The evidence for action Available at httpswwwgovukgovernmentpublicationssugar-reduction-from-evidence-into-action [accessed 19 July 2020] 111 Public Health England (2020) Coronavirus (COVID-19) emergency funding for local government Allocations of additional funding to local authorities Available at httpswwwgovukgovernmentpublicationscovid-19-emergency-funding-for-local-government [accessed 19 July 2020]

Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


2

About Public Health England Public Health England exists to protect and improve the nationrsquos health and wellbeing and reduce health inequalities We do this through world-leading science research knowledge and intelligence advocacy partnerships and the delivery of specialist public health services We are an executive agency of the Department of Health and Social Care and a distinct delivery organisation with operational autonomy We provide government local government the NHS Parliament industry and the public with evidence-based professional scientific and delivery expertise and support Public Health England Wellington House 133-155 Waterloo Road London SE1 8UG Tel 020 7654 8000 wwwgovukphe Twitter PHE_uk Facebook wwwfacebookcomPublicHealthEngland Prepared by Jamie Blackshaw Alison Feeley Lisa Mabbs Paul Niblett Elizabeth Atherton Rachel Elsom Estella Hung Dr Alison Tedstone and other members of PHE

copy Crown copyright 2020 You may re-use this information (excluding logos) free of charge in any format or medium under the terms of the Open Government Licence v30 To view this licence visit OGL Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned Published July 2020 PHE publications PHE supports the UN gateway number GW-1405 Sustainable Development Goals


3

Contents

Acknowledgements 4

Glossary of terms 5

Executive summary 6

Key insights 9

1 Introduction 11










References 56


4

Acknowledgements



5

Glossary of terms










6

Executive summary



7



8



9

Key insights











Hospitalisation




10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




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50












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52











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Sattar et al (2020)




56

References



57



58



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61



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67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


3

Contents

Acknowledgements 4

Glossary of terms 5

Executive summary 6

Key insights 9

1 Introduction 11










References 56


4

Acknowledgements



5

Glossary of terms










6

Executive summary



7



8



9

Key insights











Hospitalisation




10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



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47



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50












51


















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Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


4

Acknowledgements



5

Glossary of terms










6

Executive summary



7



8



9

Key insights











Hospitalisation




10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





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45



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50












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52











Sattar et al (2020)

Aim(s) of study






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Sattar et al (2020)






















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Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


5

Glossary of terms










6

Executive summary



7



8



9

Key insights











Hospitalisation




10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



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50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


6

Executive summary



7



8



9

Key insights











Hospitalisation




10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


7



8



9

Key insights











Hospitalisation




10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


8



9

Key insights











Hospitalisation




10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


9

Key insights











Hospitalisation




10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


10








11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


11

1 Introduction




12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


12



13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


13






14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


14





15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


15




16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


16






17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


17



18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


18





19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


19



Men

Women

Type 2 diabetes 52

127

Hypertension 26

42


32


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


20


27

Angina 18

18


18

Ovarian cancer

17

Osteoarthritis 19

14

Stroke 13

13



21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


21


Socio-economics




22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


22

Ethnicity




23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


23



24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


24









25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


25







26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












51


















52











Sattar et al (2020)

Aim(s) of study






53


Sattar et al (2020)






















54


Sattar et al (2020)











55


Sattar et al (2020)




56

References



57



58



59



60





61



62



63



64







65



66



67


Acknowledgements

Glossary of terms

Executive summary

Key insights

1 Introduction










References


26






27




Hospitalisation



28





29



Risk of mortality



30




31






32



33





34




Thrombosis



35





36




37




38




39




40




41




42




43





44




45



46




47



48

















49



















50












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excess weight and covid-19...living with obesity to lose weight, together with interventions to...

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